Leveraging Deep Learning and IoT big data analytics to support the smart cities development: Review and future directions
The rapid growth of urban populations worldwide imposes new challenges on citizens' daily
lives, including environmental pollution, public security, road congestion, etc. New …
lives, including environmental pollution, public security, road congestion, etc. New …
Anomaly detection using edge computing in video surveillance system
The current concept of smart cities influences urban planners and researchers to provide
modern, secured and sustainable infrastructure and gives a decent quality of life to its …
modern, secured and sustainable infrastructure and gives a decent quality of life to its …
Deep learning for multigrade brain tumor classification in smart healthcare systems: A prospective survey
Brain tumor is one of the most dangerous cancers in people of all ages, and its grade
recognition is a challenging problem for radiologists in health monitoring and automated …
recognition is a challenging problem for radiologists in health monitoring and automated …
Attention based CNN model for fire detection and localization in real-world images
Fire is a severe natural calamity that causes significant harm to human lives and the
environment. Recent works have proposed the use of computer vision for develo** a cost …
environment. Recent works have proposed the use of computer vision for develo** a cost …
A modified YOLOv5 architecture for efficient fire detection in smart cities
Fire disasters are considered to be among the most harmful hazards, causing fatalities,
ecological and economic chaos, property damage, and they can even impact climate …
ecological and economic chaos, property damage, and they can even impact climate …
Light-DehazeNet: a novel lightweight CNN architecture for single image dehazing
Due to the rapid development of artificial intelligence technology, industrial sectors are
revolutionizing in automation, reliability, and robustness, thereby significantly increasing …
revolutionizing in automation, reliability, and robustness, thereby significantly increasing …
Dynamic digital twin and federated learning with incentives for air-ground networks
W Sun, N Xu, L Wang, H Zhang… - IEEE Transactions on …, 2020 - ieeexplore.ieee.org
The air-ground network provides users with seamless connections and real-time services,
while its resource constraint triggers a paradigm shift from machine learning to federated …
while its resource constraint triggers a paradigm shift from machine learning to federated …
Fire detection in video surveillances using convolutional neural networks and wavelet transform
Fire is one of the most frequent and common emergencies threatening public safety and
social development. Recently, intelligent fire detection technologies represented by …
social development. Recently, intelligent fire detection technologies represented by …
Optimized dual fire attention network and medium-scale fire classification benchmark
Vision-based fire detection systems have been significantly improved by deep models;
however, higher numbers of false alarms and a slow inference speed still hinder their …
however, higher numbers of false alarms and a slow inference speed still hinder their …
A comprehensive survey of multi-view video summarization
There has been an exponential growth in the amount of visual data on a daily basis
acquired from single or multi-view surveillance camera networks. This massive amount of …
acquired from single or multi-view surveillance camera networks. This massive amount of …